1. Field of the Invention
This invention relates to means and methods of processing an object image to extract information on the shape of the object. The invention employs successively finer levels of analysis of segments of the objects boundary by an iterative process.
2. Related Art
The problem of quantitatively describing the shape of an object is central to the field of image processing (IP). Although shape description techniques have been developed for such diverse purposes as character recognition, classification of tactical targets, and assembly line inspection, none of these systems meet current needs and the demand for improved performance at less cost.
Hu and Alt in 1962 described certain boundary moment approximtaions which exhibited rotationally invariant shape information. Using fourier boundary descriptions, Cosgriff and Brill in 1968 demonstrated that the shape of numerals could be quantified and reconstructed with varying degrees of resolution, depending on how many coefficients were used. Both the above techniques are computationally very expensive. The widely investigated Medial Axis Transformation (MAT) or skeletonization first reported by H. Blum in 1968 has also shown promise. However, it is generally conceded that MAT is very sensitive to boundary noise and generally requires presmoothing, which itself uses additional parameters that are difficult to automate.
Much research in character recognition has been founded on the premise that handwritten characters are composed of pen stroke primitives. One example of this approach is W. W. Stallings' stroke based Chinese character recognizer, "Chinese Character Recognition", Syntatic Pattern Recognition Applications, Springer-Verlag (1977) pp. 95-123. T. Pavlidis and H. Y. F. Feng in "Shape Discrimination", Syntatic Pattern Recognition Applications, Springer-Verlag (1977), pp. 125-145, reported an approach which decomposes object shape into a series of convex polygons. Although the aforementioned represent significant achievements, techniques such as polygonal decomposition and skeletonization either are frauhht with algorithmic constraints such as presmoothing or are computationally too expensive to present a realistic option for real time IP systems today. Consequently, many IP systems are forced to rely on simple features such as length to width ratio and perimeter to supply gross shape information to an object classifier. There is a clear need for a computationally inexpensive technique for extracting detailed shape information from a scene.